Lesson 107: Robot Sensing and Mapping | The Robot Doctor
Support Materials
How a robot can “see” things around it without using cameras – converting polar coordinates to cartesian coordinates in order to make a map.
Assignment: Lesson 107
Start with a 3m by 3m grid with 1m cells as shown. The robot is in the center of the bottom left cell. Initially the map has a value of 50% for all cells. Use: p(return|obstacle) = 80%, p(return|clear) = 10%
- The robot gets a lidar return from the bottom right cell – Which cells will have a change in value?
- What are the updated values for each cell?
- If the robot gets a second return from the bottom righ cell, what are the updated values now?
About
Learn how a robot can “see” things around it without using cameras—by converting polar coordinates to cartesian coordinates in order to make a map, in this 14-minute episode. The goal of this video series is to teach the basics of Robotics: the what, why, and how—with examples—and to provide take-home problems to solve.
How do robots sense their surroundings? How do they keep track of where obstacles are? In this lesson we will examine how robot sensors work and see how that information is stored in a convenient, easily updatable format that accounts for errors in the robot measurements. We will use conditional probability to calculate the updated values after we get a measurement and see how to store this in an occupancy grid.
Credits: WQED, RobotWits LLC, PA Rural Robotics, Dr. Jonathan Butzke, Carnegie Mellon University
Standards
- Interpreting sensor data (range, proximity) (STEELS.6-8.PS.2)
- Constructing maps from sensor observations (STEELS.6-8.TE.7)
- Integrating sensor fusion concepts (STEELS.9-12.TE.7)
- Designing mapping approaches aligned to tasks (STEELS.9-12.TE.5)
- Plotting points on a grid (CC.2.3.8.A.1)
- Calculating distances between points (CC.2.3.8.A.3)
- Coordinate geometry for mapping (CC.2.3.HS.A.8)
- Applying transformations for map updates (CC.2.3.HS.A.10)
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